Disease gene prediction with privileged information and heteroscedastic dropout. - Juan Shu; Yu Li 006; Sheng Wang 012; Bowei Xi; Jianzhu Ma (Bioinform., 2021)

Understanding Adversarial Examples Through Deep Neural Network's Response Surface and Uncertainty Regions. - Juan Shu; Bowei Xi; Charles A. Kamhoua (CoRR, 2021)

Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration. - Xuesong Wang; Zhihang Hu; Tingyang Yu; Ruijie Wang; Yumeng Wei; Juan Shu; Jianzhu Ma; Yu Li 006 (CoRR, 2021)

Understanding Adversarial Examples Through Deep Neural Network's Classification Boundary and Uncertainty Regions. - Juan Shu; Bowei Xi; Charles A. Kamhoua (AISafety@IJCAI, 2022)

Understanding Dropout for Graph Neural Networks. - Juan Shu; Bowei Xi; Yu Li 006; Fan Wu; Charles A. Kamhoua; Jianzhu Ma (WWW (Companion Volume), 2022)

Con-AAE: contrastive cycle adversarial autoencoders for single-cell multi-omics alignment and integration. - Xuesong Wang; Zhihang Hu; Tingyang Yu; Yixuan Wang; Ruijie Wang; Yumeng Wei; Juan Shu; Jianzhu Ma; Yu Li 006 (Bioinform., 2023)

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. - Amit Roy; Juan Shu; Jia Li 009; Carl Yang 001; Olivier Elshocht; Jeroen Smeets; Pan Li 005 (WSDM, 2024)

Time Series Treatment Effects Analysis with Always-Missing Controls. - Juan Shu; Qiyu Han; George Chen; Xihao Cao; Kangming Luo; Dan Pallotta; Shivam Agrawal; Yuping Lu; Xiaoyu Zhang; Jawad Mansoor; Jyoti Anand (PAKDD (1), 2025)